Just as data is used to help businesses determine new directions, set new goals, and measure progress, data can be used in everyday life to help people do the same as they seek to improve themselves.As the new year arrives, many people are thinking about new goals and new ways to improve their lives, so we have invited Gary Wolf to the show to explore how you can use data-driven thinking to drive meaningful changes in yourself.Gary Wolf is the Co-Founder of The Quantified Self, an international community of makers and users of self-tracking tools. Prior to co-founding The Quantified Self, Wolf was a contributing editor for Wired Magazine, where he spent two decades covering the intersection of technology and culture, and his cover story in the New York Times is what introduced the general public to self-tracking as an emerging trend.In this episode, we talk about what The Quantified Self is, why self-tracking projects can be life-changing, how to get started with self-tracking, how to connect with others in the self-tracking community, and much more.

Gary Wolf, founder of the Quantified Self and director of the Article 27 Foundation, discusses the transformative power of personal science and self-tracking. He delves into how the Quantified Self movement encourages individuals to harness their data for better health insights. Wolf highlights the role of participant-led research in bridging the gap between clinical and public health, and explores the implications of artificial intelligence in advancing personal health decisions. His views on smart wearables and community engagement add a compelling angle to understanding our health in the digital age.

Rachel Kalmar, a neuroscientist and wearable tech expert, joins Gary Wolf, co-founder of the Quantified Self movement, and Geoffrey Woo, biohacking innovator, to discuss the evolution of health wearables. They explore how emerging technologies like VR and continuous glucose monitors are revolutionizing self-tracking and personalized healthcare. The conversation highlights the challenges of data interpretation and user adoption, while also pondering the societal implications of a more quantified lifestyle and the potential shift towards mainstream acceptance of biohacking.